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Open AccessJournal ArticleDOI

The K Function Methods on a Network

Ikuho Yamada, +1 more
- 31 Mar 2000 - 
- Vol. 8, Iss: 1, pp 75-82
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TLDR
The objective of this paper is to propose new methods for analyzing relationships between point objects distributed on a network using the K function method, which is used to analyze a distribution of point objects on a continuous plane.
Abstract
The objective of this paper is to propose new methods for analyzing relationships between point objects distributed on a network.First, the K function method, which is used to analyze a distribution of point objects on a continuous plane, is extended into the network K function method to be applied to a distribution on a network. Second, the network cross K function method is defined as a method that deals with the relationship between two distributions of point objects on a network. Third, a computational method for the network K function methods is proposed.

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Citations
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Journal ArticleDOI

Spatial heterogeneity assessment of factors affecting sewer pipe blockages and predictions.

TL;DR: In this paper, a spatial statistical approach to determine the influence of explanatory factors on increased blockage propensity in sewers based on spatial heterogeneity was investigated, which provided an understanding of the significance of the spatial variation of blockages.
Journal ArticleDOI

Spatial Analysis in GIS Environments

TL;DR: Various computational methods for spatial analysis, such as the nearest neighbor distance, K-function, Voronoi's tessellation, and Huff-based marketing methods, are discussed, which are all found at the FreeSAT site.
Book ChapterDOI

Extension of Spatial Correlation Analysis to Road Network Spaces

TL;DR: A method for applying spatial correlation analysis to a road-network space and the details of computation methods are discussed and a comparison of the results from the Euclidean distance and the network distance is shown.
References
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Book

Spatial statistics

Book

Interactive Spatial Data Analysis

TL;DR: A: Introduction 1. Spatial data analysis 2. Computers and Spatial Data Analysis B: The Analysis of Data Associated with Points 3. Methods Relating to Point Patterns 4. Methodsrelating to Marked Point Patterns 5. MethodsRelating to a Continuously Varying Attribute Sampled at Points.
Proceedings ArticleDOI

Fibonacci Heaps And Their Uses In Improved Network Optimization Algorithms

TL;DR: The structure, Fibonacci heaps (abbreviated F-heaps), extends the binomial queues proposed by Vuillemin and studied further by Brown to obtain improved running times for several network optimization algorithms.
Journal ArticleDOI

Statistical Analysis of the Distribution of Points on a Network

TL;DR: In this paper, four statistical methods that examine the distribution of points on a network (e.g., distribution of retail stores along streets) are presented. But they do not consider the effect of infrastructural elements (such as railway stations and big parks) on the distributions of activity points on networks.
Journal ArticleDOI

The Multi Nearest Neighbor Distance Method for Analyzing the Compound Effect of Infrastructural Elements on the Distribution of Activity Points

TL;DR: A statistical method to analyze the compound effect of infrastructural elements on the distribution of activity points over a region and develops multivariate statistical methods for testing several hypotheses about these compound effects.
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